What This Article Covers
- The Background on the Brightwork MRP & S&OP Explorer
- Constrained Versus Unconstrained Forecast Error
- Using the Brightwork MRP + S&OP Explorer
- S&OP to the Rescue?
ERP systems and even advanced planning systems normally do not provide the type of high-level descriptive statistics that are important and figuring out supply chain planning quality and areas to improve. Rather, they are focused on meeting the needs of planners often to evaluate specific product location combinations. It is surprising how many vendors have missed the critical workflows that are standard in Brightwork Explorer.
- Brightwork Explorer can tell you how efficiently your inventory is being deployed.
- It can tell you where are you over investing in stock?
- Where are you under-investing in inventory?
We roll this up into an inventory effectiveness score for each product location combination.
What is the overall inventory efficiency score of your supply chain planning process? Find out with the Brightwork Inventory Explorer Score. After you have determined your score, move to the Brightwork MRP Explorer to improve your score by making changes to service levels, days of supply and MRP parameters.
Should the forecasting process be held accountable for forecasting demand, or for forecasting the constraints of the company? Because if the demand history is not adjusted upward in the right places, the constraint (saved as the booked sales order) becomes the previous demand.
Constrained Versus Unconstrained Forecast Error
The vast majority of companies maintain their sales history. Their sales history is what was sold. This is called the constrained forecast. In supply chain planning software, the only constraining capacity is within the supply planning application (this is either ERP or external supply planning application).
This presents several problems. One is that the demand is higher than sales orders. The sales orders are what was sold, but it was not necessarily what was demanded. Let us use an example:
- Company A created a forecast of 10 units for February at a product location.
- Due to either production capacity constraints or supplier capacity constraints, only five units could be made available for February.
- In this scenario, there is no back order as the customer goes to a different seller (any number of scenarios are possible, the customer could substitute, they could backorder, or they could go to a different customer, or they could just postpone their purchase. But here we will go with the seller losing the sale, and not getting the sale in later months)
The measure of forecast accuracy is the measure of the effectiveness of the overall forecasting process. The measure of a specific forecast accuracy input, such as the accuracy of the sales forecast input, is a measure of the effectiveness of a subset of the forecasting process. If the overall forecasting process (in this case) would have attained a 100% forecast accuracy, but due to constraints, the resulting forecast accuracy is 50%, then the forecasting process is unfairly maligned. And here are several problems with this:
- It will provide a false signal that perhaps the forecasting process should be addressed, when in fact (in this case) it is perfectly fine.
- It will mean that the demand history is only what the company did sell, not what the company could have sold. This means that there will have to be more manual intervention into the forecast as the statistical methods that are applied will reproduce too low of a level. It will also mean inaccurate signaling as items that were substituted for the primary item that was demanded will be over forecasted in the future (at least statistically) while the initially demanded item will be under forecasted in the future (at least statistically).
This is the problem with only measuring unconstrained forecast error. But the problem is what to do about it. Companies normally do not have a good way of measuring lost sales; it means that the forecast error is exaggerated to the degree that the company is capacity constrained.
S&OP to the Rescue?
It is often stated that a “good S&OP process,” addresses this issue. But does it? An S&OP process will bring the forecast down to meet the capacity. That balances the plan, making sure it is attainable, but that does not, in fact, address the issue. In fact, it hides the issue.
Addressing the issue would mean keeping a separate data stream which accounts for lost sales. It also means having a way to measuring the forecast error of lost sales. This can come from estimating lost sales from the demand history based upon inputs from order management, as this type of information is only very rarely inside of the order management system itself.
Once the data is obtained, now the error measurement is where Brightwork Explorer comes in to play. Lost sales + sales orders can be fed into Brightwork Explorer, and its error checked against the forecast. This provides a far more accurate representation of the relevant forecast error and allows companies to focus in on areas of forecasting shortcomings, rather than be misdirected into focusing on areas where the unconstrained forecast is inaccurate due to capacity constraints.
Using the Brightwork MRP + S&OP Explorer
The Brightwork MRP Explorer does something that no other software on the market does. That is right, not software that uses MRP, nor heuristics, nor allocation, nor cost optimization, nor inventory optimization allow for setting MRP parameters in concert with objectives. We would know as we have written books on every one of these methods.
In fact, we developed the Brightwork MRP Explorer after working on and reviewing many projects with the approaches mentioned above.
Brightwork MRP Explorer is not designed to replace the supply planning system you have. We do not create planned production orders or purchase requisitions. Instead, we tune your system, making it better, and allowing it to run with far less effort and maintenance, freeing up your planners to focus on specific items, as the overall system is managed for them.